Dataset Preview
The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
The dataset generation failed because of a cast error
Error code: DatasetGenerationCastError
Exception: DatasetGenerationCastError
Message: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 2 new columns ({'demo_age_5_17', 'demo_age_17_'}) and 2 missing columns ({'bio_age_5_17', 'bio_age_17_'}).
This happened while the csv dataset builder was generating data using
hf://datasets/gani2004/data/datahackthon/api_data_aadhar_demographic/api_data_aadhar_demographic/api_data_aadhar_demographic_0_500000.csv (at revision c4eb8776c433889b0f6d23d97bdee24f9ca4ec44)
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1831, in _prepare_split_single
writer.write_table(table)
File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 714, in write_table
pa_table = table_cast(pa_table, self._schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2272, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2218, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
date: string
state: string
district: string
pincode: int64
demo_age_5_17: int64
demo_age_17_: int64
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 952
to
{'date': Value('string'), 'state': Value('string'), 'district': Value('string'), 'pincode': Value('int64'), 'bio_age_5_17': Value('int64'), 'bio_age_17_': Value('int64')}
because column names don't match
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1339, in compute_config_parquet_and_info_response
parquet_operations = convert_to_parquet(builder)
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 972, in convert_to_parquet
builder.download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 894, in download_and_prepare
self._download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 970, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1702, in _prepare_split
for job_id, done, content in self._prepare_split_single(
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1833, in _prepare_split_single
raise DatasetGenerationCastError.from_cast_error(
datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 2 new columns ({'demo_age_5_17', 'demo_age_17_'}) and 2 missing columns ({'bio_age_5_17', 'bio_age_17_'}).
This happened while the csv dataset builder was generating data using
hf://datasets/gani2004/data/datahackthon/api_data_aadhar_demographic/api_data_aadhar_demographic/api_data_aadhar_demographic_0_500000.csv (at revision c4eb8776c433889b0f6d23d97bdee24f9ca4ec44)
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
date string | state string | district string | pincode int64 | bio_age_5_17 int64 | bio_age_17_ int64 |
|---|---|---|---|---|---|
01-03-2025 | Haryana | Mahendragarh | 123,029 | 280 | 577 |
01-03-2025 | Bihar | Madhepura | 852,121 | 144 | 369 |
01-03-2025 | Jammu and Kashmir | Punch | 185,101 | 643 | 1,091 |
01-03-2025 | Bihar | Bhojpur | 802,158 | 256 | 980 |
01-03-2025 | Tamil Nadu | Madurai | 625,514 | 271 | 815 |
01-03-2025 | Maharashtra | Ratnagiri | 416,702 | 155 | 529 |
01-03-2025 | Gujarat | Anand | 388,130 | 75 | 143 |
01-03-2025 | Gujarat | Gandhinagar | 382,421 | 192 | 298 |
01-03-2025 | Odisha | Dhenkanal | 759,025 | 122 | 214 |
01-03-2025 | Gujarat | Valsad | 396,055 | 67 | 85 |
01-03-2025 | Tamil Nadu | Salem | 636,119 | 103 | 63 |
01-03-2025 | West Bengal | Hooghly | 712,414 | 91 | 97 |
01-03-2025 | West Bengal | Paschim Medinipur | 721,147 | 86 | 116 |
01-03-2025 | Kerala | Wayanad | 670,721 | 75 | 293 |
01-03-2025 | Rajasthan | Sawai Madhopur | 322,027 | 108 | 300 |
01-03-2025 | Bihar | Vaishali | 844,504 | 426 | 958 |
01-03-2025 | Tamil Nadu | Karur | 639,105 | 131 | 103 |
01-03-2025 | Punjab | Rupnagar | 140,118 | 38 | 97 |
01-03-2025 | Gujarat | Sabarkantha | 383,440 | 56 | 91 |
01-03-2025 | Himachal Pradesh | Una | 177,039 | 24 | 30 |
01-03-2025 | Rajasthan | Bhilwara | 311,805 | 52 | 64 |
01-03-2025 | Uttar Pradesh | Bara Banki | 225,408 | 17 | 3 |
01-03-2025 | Assam | Cachar | 788,106 | 21 | 24 |
01-03-2025 | Uttarakhand | Dehradun | 248,146 | 13 | 17 |
01-03-2025 | Himachal Pradesh | Chamba | 176,302 | 83 | 101 |
01-03-2025 | Madhya Pradesh | Shajapur | 465,339 | 234 | 153 |
01-03-2025 | Tamil Nadu | The Nilgiris | 643,231 | 53 | 59 |
01-03-2025 | Maharashtra | Wardha | 442,101 | 269 | 538 |
01-03-2025 | Odisha | Nabarangapur | 764,075 | 438 | 605 |
01-03-2025 | Punjab | Shaheed Bhagat Singh Nagar | 144,514 | 134 | 249 |
01-03-2025 | Karnataka | Davangere | 577,002 | 219 | 386 |
01-03-2025 | Gujarat | Dahod | 389,382 | 341 | 569 |
01-03-2025 | Tamil Nadu | Tiruppur | 641,654 | 307 | 415 |
01-03-2025 | Haryana | Mahendragarh | 123,001 | 454 | 730 |
01-03-2025 | Andhra Pradesh | Vizianagaram | 535,592 | 77 | 72 |
01-03-2025 | Punjab | Moga | 142,041 | 69 | 138 |
01-03-2025 | Gujarat | Rajkot | 363,630 | 17 | 79 |
01-03-2025 | Telangana | Hyderabad | 500,013 | 581 | 654 |
01-03-2025 | Odisha | Sundergarh | 769,004 | 152 | 186 |
01-03-2025 | Andhra Pradesh | Kurnool | 518,385 | 291 | 138 |
01-03-2025 | Kerala | Wayanad | 673,121 | 130 | 225 |
01-03-2025 | Andhra Pradesh | Warangal | 506,163 | 39 | 92 |
01-03-2025 | Tamil Nadu | Tirunelveli | 627,108 | 238 | 435 |
01-03-2025 | Goa | South Goa | 403,601 | 183 | 188 |
01-03-2025 | Andhra Pradesh | Anantapur | 515,301 | 83 | 105 |
01-03-2025 | Kerala | Thiruvananthapuram | 695,303 | 71 | 78 |
01-03-2025 | Andhra Pradesh | Srikakulam | 532,459 | 362 | 161 |
01-03-2025 | Telangana | Nizamabad | 503,164 | 399 | 120 |
01-03-2025 | Odisha | Cuttack | 753,003 | 40 | 112 |
01-03-2025 | Rajasthan | Baran | 325,216 | 438 | 580 |
01-03-2025 | Andhra Pradesh | Guntur | 522,329 | 126 | 55 |
01-03-2025 | Karnataka | Mysuru | 571,602 | 117 | 131 |
01-03-2025 | West Bengal | Purba Medinipur | 721,441 | 49 | 53 |
01-03-2025 | Kerala | Ernakulam | 682,508 | 48 | 64 |
01-03-2025 | Madhya Pradesh | Balaghat | 481,335 | 328 | 401 |
01-03-2025 | Tamil Nadu | Sivaganga | 630,106 | 59 | 58 |
01-03-2025 | Bihar | Bhojpur | 802,164 | 165 | 311 |
01-03-2025 | Tamil Nadu | Tirunelveli | 627,761 | 46 | 36 |
01-03-2025 | Madhya Pradesh | Harda * | 461,441 | 30 | 143 |
01-03-2025 | Nagaland | Mokokchung | 798,613 | 18 | 70 |
01-03-2025 | Karnataka | Uttara Kannada | 581,344 | 15 | 7 |
01-03-2025 | Tamil Nadu | Perambalur | 621,113 | 198 | 80 |
01-03-2025 | Karnataka | Udupi | 574,114 | 16 | 16 |
01-03-2025 | Andhra Pradesh | Ananthapur | 515,261 | 58 | 11 |
01-03-2025 | Tamil Nadu | Coimbatore | 642,104 | 55 | 55 |
01-03-2025 | Jharkhand | West Singhbhum | 833,213 | 93 | 70 |
01-03-2025 | Karnataka | Tumakuru | 572,225 | 16 | 3 |
01-03-2025 | West Bengal | Birbhum | 731,244 | 46 | 52 |
01-03-2025 | Andhra Pradesh | Visakhapatnam | 530,045 | 50 | 134 |
01-03-2025 | Uttar Pradesh | Hardoi | 241,406 | 803 | 216 |
01-03-2025 | Uttar Pradesh | Siddharthnagar | 272,205 | 857 | 272 |
01-03-2025 | Jharkhand | Dhanbad | 828,304 | 44 | 118 |
01-03-2025 | Bihar | Darbhanga | 846,003 | 438 | 859 |
01-03-2025 | Madhya Pradesh | Jabalpur | 482,002 | 458 | 678 |
01-03-2025 | West Bengal | North 24 Parganas | 743,145 | 127 | 234 |
01-03-2025 | Uttar Pradesh | Hardoi | 241,304 | 1,025 | 328 |
01-03-2025 | Karnataka | Tumkur | 572,175 | 25 | 56 |
01-03-2025 | Jammu and Kashmir | Leh | 194,401 | 52 | 43 |
01-03-2025 | Andhra Pradesh | West Godavari | 534,316 | 134 | 73 |
01-03-2025 | Haryana | Kaithal | 136,044 | 235 | 368 |
01-03-2025 | Gujarat | Kachchh | 370,140 | 392 | 286 |
01-03-2025 | Andhra Pradesh | Krishna | 521,401 | 109 | 125 |
01-03-2025 | Karnataka | Davangere | 577,001 | 318 | 517 |
01-03-2025 | Kerala | Kannur | 670,633 | 22 | 52 |
01-03-2025 | Karnataka | Shivamogga | 577,401 | 62 | 50 |
01-03-2025 | West Bengal | Bankura | 722,151 | 178 | 160 |
01-03-2025 | Rajasthan | Rajsamand | 313,331 | 454 | 345 |
01-03-2025 | Kerala | Thiruvananthapuram | 695,582 | 33 | 90 |
01-03-2025 | Assam | Cachar | 788,123 | 15 | 21 |
01-03-2025 | Karnataka | Davangere | 577,003 | 39 | 87 |
01-03-2025 | Tamil Nadu | Namakkal | 636,203 | 49 | 51 |
01-03-2025 | Tamil Nadu | Thiruvarur | 614,704 | 174 | 105 |
01-03-2025 | Telangana | Karimnagar | 505,331 | 68 | 77 |
01-03-2025 | Assam | South Salmara Mankachar | 783,131 | 63 | 49 |
01-03-2025 | Himachal Pradesh | Shimla | 171,201 | 42 | 54 |
01-03-2025 | Telangana | Nalgonda | 508,210 | 69 | 64 |
01-03-2025 | Bihar | Saharsa | 852,210 | 58 | 118 |
01-03-2025 | Tamil Nadu | Kanniyakumari | 629,165 | 40 | 115 |
01-03-2025 | Telangana | Medak | 502,280 | 32 | 46 |
01-03-2025 | Telangana | Warangal | 506,015 | 31 | 29 |
End of preview.
No dataset card yet
- Downloads last month
- 13